CN112886636B - P2X modeling and optimizing method for high-proportion renewable energy power system - Google Patents

P2X modeling and optimizing method for high-proportion renewable energy power system Download PDF

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CN112886636B
CN112886636B CN202110114093.0A CN202110114093A CN112886636B CN 112886636 B CN112886636 B CN 112886636B CN 202110114093 A CN202110114093 A CN 202110114093A CN 112886636 B CN112886636 B CN 112886636B
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CN112886636A (en
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姜海洋
杜尔顺
张宁
康重庆
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Tsinghua University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

Abstract

The invention relates to a P2X modeling and optimizing method for a high-proportion renewable energy power system, and belongs to the technical field of power system optimization planning. Firstly, constructing P2X electric energy preparation constraint, seasonal X energy storage annual time sequence coupling operation constraint and X inter-area transfer constraint corresponding to each X to form a P2X model corresponding to the X; then, establishing a power system planning optimization model considering the operation of P2X, and embedding a P2X model corresponding to each X as a constraint condition into the model; and solving the model to obtain an optimal planning scheme of the power system. The method considers the influence of the introduction of the multi-type P2X on the dispatching operation of the power system in the traditional power system planning optimization model, is beneficial to scientifically configuring the line capacity of the generator set by power design and operation dispatching personnel, effectively analyzes the P2X dispatching operation condition in the power system, and reasonably arranges the coordinated output of each type of generator set, thereby ensuring the renewable energy consumption level in the power system.

Description

P2X modeling and optimizing method for high-proportion renewable energy power system
Technical Field
The invention relates to a P2X modeling and optimizing method for a high-proportion renewable energy power system, and belongs to the technical field of power system optimization planning.
Background
The construction of green, low-carbon and clean energy systems mainly based on renewable energy is an energy strategic choice in China and even all over the world, and the high-proportion renewable energy grid connection (the renewable energy ratio in the invention exceeds 30%) becomes the basic characteristic of a future power system. The renewable energy power generation and the power load of the power system have seasonal variation characteristics, which brings challenges to effective consumption of large-scale renewable energy power. On the other hand, the traditional industries such as metallurgy and chemical industry depend on fossil energy such as coal, petroleum and natural gas. The widespread use of fossil energy has brought tremendous carbon emissions pressure to industrial production, and has brought serious challenges to global energy safety and climate change. P2X (Power to X, electric Power multi-element conversion technology taking clean energy as a main body) replaces the traditional industrial production depending on fossil energy through electrification in the chemical industry, various inorganic and organic raw materials and fuel (X) are prepared by electric energy generated by the clean energy and are stored for a long time in a large scale, a large-scale consumption way is hopefully provided for renewable energy sources such as wind and light while carbon emission is reduced, and equivalent large-scale seasonal storage and multi-energy interconnection of the electric energy are realized. Therefore, an energy development, configuration and utilization system taking clean energy power as a leading factor is established, and the method is an effective way for realizing large-scale consumption of renewable energy in a future power system.
Currently, the P2X technology is a research hotspot in academia. A hydrogen energy supply chain constructed based on an electrical hydrogen production technology and seasonal hydrogen storage equipment and a clean heat supply system constructed based on clean electric power heat supply and combined with the seasonal heat storage technology are researched to a certain extent. However, these studies rarely analyze the influence of the P2X technology on the optimal operation of the power system, and it is difficult to evaluate and consider the annual time series coupling operation characteristics of the power system in which P2X is matched with seasonal X energy storage, and also unable to analyze the influence of the spatial dynamic distribution of the X energy storage resource on the effective consumption of renewable energy.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a P2X modeling and optimizing method for a high-proportion renewable energy power system. The method can consider the influence of the introduction of the multi-type P2X on the scheduling operation of the power system in the traditional power system planning optimization model; power design and operation scheduling personnel can scientifically configure the line capacity of the generator set according to the method, effectively analyze the P2X scheduling operation condition in the power system, and reasonably arrange the coordinated output of various generator sets, thereby ensuring the renewable energy consumption level in the power system, reducing the wind and light abandonment of the system and improving the value of energy utilization from the perspective of an all-round source-matter system.
The invention provides a P2X modeling and optimizing method for a high-proportion renewable energy power system, which is characterized in that firstly, aiming at each X prepared by electric energy, a P2X electric energy preparation constraint corresponding to the X, a seasonal X energy storage annual time sequence coupling operation constraint and an X inter-region transfer constraint are respectively constructed, and a P2X model corresponding to each X is formed; then establishing an electric power system planning optimization model considering P2X operation, wherein the objective function of the model is the minimization of the total cost, and the constraint conditions comprise node power balance constraint, power transmission network constraint, conventional thermal power unit operation constraint, renewable energy output constraint, electrochemical energy storage operation constraint and supply chain system balance equation constraint of each X; embedding the P2X model corresponding to each X into the model as a P2X model and operation constraints; and solving the optimization model to obtain an optimal planning scheme of the power system. The method comprises the following steps:
1) respectively establishing a P2X model corresponding to each X prepared by electric energy; the method comprises the following specific steps:
1-1) constraint of P2X electric energy:
Figure BDA0002919986950000021
wherein, the superscript X represents different types of energy and substances obtained by energy conversion by utilizing the P2X technology, and Cha represents the charging state of X stored energy; subscript x represents P2X equipment number, m represents month number, d represents day number, t represents time number, and N represents grid node type; collection of
Figure BDA0002919986950000022
Represents the set of grid nodes connected to P2X device x; i TDL represents the total number of time periods participating in the operation analysis in a day;
Figure BDA0002919986950000023
showing the energy conversion efficiency of the P2X plant X for making X,
Figure BDA0002919986950000024
P2X equipment for preparing XxThe consumed power at d days t of m months,
Figure BDA0002919986950000025
indicating the utilization of the P2X device on d days of m monthsxPreparing X and storing the X;
wherein the content of the first and second substances,
Figure BDA0002919986950000026
wherein the content of the first and second substances,
Figure BDA0002919986950000027
represents the upper power capacity limit of the P2X plant X for the production of X;
1-2) seasonal X energy storage annual time sequence coupling operation constraint; the method specifically comprises the following steps:
energy balance constraint between adjacent days in seasonal energy storage month:
Figure BDA0002919986950000028
wherein Dis represents the energy release state of X energy storage, and p represents the transportation path of X; collection
Figure BDA0002919986950000031
Representing the collection of transport paths carried out by P2X plant X making X,
Figure BDA0002919986950000032
representing a set of transport paths taken by a P2X plant X making X;
Figure BDA0002919986950000033
representing the energy storage loss rate of P2X device X storing X,
Figure BDA0002919986950000034
indicating that P2X device X stores X's reserves on d days of m months,
Figure BDA0002919986950000035
respectively representing that X is obtained by P2X equipment X on d days of m months and stored and releasedThe amount of (a) to (b) is,
Figure BDA0002919986950000036
represents the X traffic through the transport path p at d days m months;
P2X device adjacent monthly energy balance constraints:
Figure BDA0002919986950000037
wherein, delta represents the time consumption of X transportation between areas, | M | represents the upper limit of the month number, the value is 12, | DmI represents the upper limit of the day number value of the mth month;
the starting and ending reserves balance constraint expressions for the P2X device at the annual time scale are as follows:
Figure BDA0002919986950000038
1-3) inter-regional transport constraints of X:
Figure BDA0002919986950000039
1-4) for each X, the joint type (1) - (6) forms a P2X model corresponding to the X;
2) establishing a power system planning optimization model considering the operation of P2X, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
2-1) determining an objective function of the optimization model:
min(CInv+COpe+CCur) (7)
wherein, CInvRepresents annual investment cost of the power system, COpeRepresents the annual operating cost of the power system, CCurRepresenting a load shedding penalty cost; wherein the content of the first and second substances,
CInv＝CInv,G+CInv,W+CInv,PV+CInv,L+CInv,B+CInv,X (8)
wherein, CInv,GAnnual investment for conventional thermal power generating units, CInv,WAnnual investment for wind turbines, CInv,PVAnnual investment of photovoltaic units, CInv,LFor annual investment in transmission lines, CInv,BAnnual investment for electrochemical energy storage, CInv,XAnnual investment for P2X and seasonal energy storage equipment; the calculation expressions are respectively as follows:
Figure BDA0002919986950000041
Figure BDA0002919986950000042
Figure BDA0002919986950000043
Figure BDA0002919986950000044
Figure BDA0002919986950000045
Figure BDA0002919986950000046
wherein G, W, PV, L, B, X respectively represent the numbers of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic power generating unit, a power transmission line, an electrochemical energy storage device and a P2X device, | G |, | W |, | PV |, | L |, | B |, | X | respectively represent the numbers of the conventional thermal power generating unit, the wind power generating unit, the photovoltaic power generating unit, the power transmission line, the electrochemical energy storage device and the P2X device, and the upper labels G, W, PV, L, B, X respectively represent the electric power device categories of the conventional thermal power generating unit, the wind power generating unit, the photovoltaic power generating unit, the power transmission line, the electrochemical energy storage device and the P2X device;
Figure BDA0002919986950000047
represents the annual unit investment cost of the g installed capacity of the conventional thermal power generating unit,
Figure BDA0002919986950000048
representing the annual unit investment cost of the installed capacity of the wind turbine,
Figure BDA0002919986950000049
represents the annual unit investment cost of the installed capacity of the PV unit,
Figure BDA00029199869500000410
represents the annual unit investment cost of the l capacity of the transmission line,
Figure BDA00029199869500000411
represents the annual unit investment cost of the power capacity of the electrochemical energy storage device b,
Figure BDA00029199869500000412
represents the annual unit investment cost of the energy capacity of the electrochemical energy storage device b,
Figure BDA00029199869500000413
representing the annual unit investment cost of the power capacity of P2X plant x,
Figure BDA00029199869500000414
annual unit investment cost representing the energy capacity of P2X plant x;
Figure BDA00029199869500000415
represents the investment capacity of the conventional thermal power generating unit g,
Figure BDA00029199869500000416
representing the investment capacity of the wind turbine w,
Figure BDA00029199869500000417
represents the investment capacity of the photovoltaic unit pv,
Figure BDA00029199869500000418
the investment capacity of the transmission line/is represented,
Figure BDA00029199869500000419
representing the power investment capacity of the electrochemical energy storage device b,
Figure BDA00029199869500000420
representing the energy investment capacity of the electrochemical energy storage device b,
Figure BDA00029199869500000421
representing the power investment capacity of P2X plant x,
Figure BDA00029199869500000422
represents the energy investment capacity of P2X plant x;
COpe＝COpe,E+COpe,X (15)
wherein, COpe,ERepresents the annual operating cost, C, of the power systemOpe,XRepresents the annual operating cost of the X supply chain; the calculation expressions are respectively as follows:
Figure BDA0002919986950000051
wherein the content of the first and second substances,
Figure BDA0002919986950000052
represents the unit fuel cost of the electricity generation of the conventional thermal power generating unit g,
Figure BDA0002919986950000053
representing the power generation power of the conventional thermal power generating unit g at m months, d days and t;
Figure BDA0002919986950000054
wherein the content of the first and second substances,
Figure BDA0002919986950000055
represents the unit transportation cost of X on the transportation path p;
Figure BDA0002919986950000056
represents the unit cost of charging and discharging energy of the P2X device x in the operation process,
Figure BDA0002919986950000057
represents the unit cost of the traditional fossil energy supply X;
Figure BDA0002919986950000058
representing the amount of X transported over path p at d days of m months,
Figure BDA0002919986950000059
represents the amount of P2X device X supplied X by conventional fossil energy on days of m months d;
Figure BDA00029199869500000510
wherein N represents the number of the grid nodes, | N | represents the total number of the grid nodes, VoLL represents the unit load shedding penalty cost,
Figure BDA00029199869500000511
representing the load shedding power of the node n at d days t of m months;
2-2) determining the constraint conditions of the optimization model, specifically as follows:
2-2-1) node power balance constraints:
Figure BDA00029199869500000512
Figure BDA00029199869500000513
wherein, aggregate
Figure BDA00029199869500000514
Respectively representing the topological connection relations of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic unit, electrochemical energy storage equipment and P2X equipment and a node n;
Figure BDA00029199869500000515
a line set which represents the power flow reference direction of the transmission line l and takes the node n as a starting node,
Figure BDA00029199869500000516
representing a line set of a power flow reference direction of the power transmission line l and taking the node n as a termination node;
Figure BDA00029199869500000517
respectively representing the generating power of a conventional thermal power generating unit g, a wind power generating unit w and a photovoltaic power generating unit pv at d days t of m months,
Figure BDA0002919986950000061
respectively representing the charging power and the discharging power of the electrochemical energy storage device b at the time of m months, d days and t,
Figure BDA0002919986950000062
represents the power consumed by P2X device x during the m months d days t, Fl,m,d,tRepresenting the power flow of the transmission line l at D days t of m months, Dn,m,d,tRepresenting the load power of the node n at d days t of m months,
Figure BDA0002919986950000063
representing the load shedding power of the node n at d days t of m months;
2-2-2) power transmission network constraints:
Figure BDA0002919986950000064
Figure BDA0002919986950000065
Figure BDA0002919986950000066
wherein, thetan,m,d,tRepresents the power angle, x, of the node n at d, t, m monthslRepresents the reactance of line l;
Figure BDA0002919986950000067
representing the upper limit of the tidal current power of the line l;
2-2-3) conventional thermal power generating unit operation constraint:
Figure BDA0002919986950000068
wherein the content of the first and second substances,
Figure BDA0002919986950000069
respectively representing the upper limit and the lower limit of the output power of the conventional thermal power generating unit g;
2-2-4) renewable energy output constraint:
Figure BDA00029199869500000610
Figure BDA00029199869500000611
wherein
Figure BDA00029199869500000612
Represents the upper limit of the predicted output of the wind turbine generator w at the time of m months, d days and t,
Figure BDA00029199869500000613
representing the upper limit of the predicted output of the photovoltaic unit pv at the time of m months, d days and t;
2-2-5) electrochemical energy storage operation constraint:
Figure BDA00029199869500000614
wherein
Figure BDA00029199869500000615
Representing the stored energy of the electrochemical energy storage device b at d days t of m months,
Figure BDA00029199869500000616
represents the charge-discharge efficiency of the electrochemical stored energy b;
Figure BDA00029199869500000617
Figure BDA00029199869500000618
Figure BDA00029199869500000619
2-2-6) P2X model and operating constraints;
taking the P2X corresponding to each X obtained in the step 1) as a P2X model and operation constraint;
2-2-7) supply chain system balance equation constraints for each X:
Figure BDA0002919986950000071
wherein
Figure BDA0002919986950000072
Representing the X load demand of P2X device X corresponding to d days m months;
3) solving the model established in the step 2) to obtain
Figure BDA0002919986950000073
As an optimum value of the investment capacity of each equipment, and
Figure BDA0002919986950000074
the optimal solution of the method is used as the optimal value of the power of each device, and finally the optimal planning scheme is obtained.
The invention has the characteristics and beneficial effects that:
1) the invention establishes a unified P2X model, and analyzes the characteristics of the participation of a plurality of types of P2X in the operation of the power system;
2) the seasonal X energy storage charging and discharging characteristic based on the annual balance is described by adopting annual time sequence coupling operation constraint;
3) the invention establishes X cross-space transfer constraint and quantitatively analyzes the operating characteristics of the dynamic change of transportable stored energy between regions;
4) the invention embeds the proposed P2X model into an electric power system optimization planning model, and proposes an electric power system planning operation analysis method based on annual time sequence coupling and energy-traffic coupling constraint;
compared with the prior art, the invention has the following advantages:
the method can consider the influence of the introduction of the multi-type P2X on the scheduling operation of the power system in the traditional power system planning optimization model; and starting from a time scale and a space scale, establishing an operation constraint based on P2X and seasonal X energy storage thereof in the power system, and adding the operation constraint into a constraint condition of a power system planning optimization model. By solving the optimization model, the power consumption condition of renewable energy sources in the power system can be effectively analyzed, the coordinated output of various generator sets is reasonably arranged, and the running economy and environmental protection of the power system are improved; compared with the existing related research, the method provided by the invention can provide theoretical basis and technical support for the optimization planning based on the P2X technology in a future high-proportion renewable energy power system. Power design and operation scheduling personnel can scientifically configure the line capacity of the generator set according to the method, effectively analyze the P2X scheduling operation condition in the power system, and reasonably arrange the coordinated output of various generator sets, thereby ensuring the renewable energy consumption level in the power system, reducing the wind and light abandonment of the system and improving the value of energy utilization from the perspective of an all-round source-matter system.
Detailed Description
The invention provides a P2X modeling and optimizing method for a high-proportion renewable energy power system, which comprises the following steps:
1) establishing a unified P2X model for each X;
according to the method, a constraint is established to form a unified P2X model aiming at links of electric energy preparation, storage, transportation and the like of different X; for each type of X, the following constraints are established:
1-1) constraint of P2X electric energy:
for different types of P2X industrial production processes, modeling input electric power and output X of P2X from the perspective of power planning, and establishing an electric energy preparation constraint equation of X as shown in formula (1):
Figure BDA0002919986950000081
in the formula (32), the superscript X represents different types of energy/substances obtained by energy conversion by using a P2X technology, and Cha represents the charging state of X stored energy; subscript x represents P2X equipment number, m represents month number, d represents day number, t represents time number, and N represents grid node type; collection
Figure BDA0002919986950000082
Represents the set of grid nodes connected to P2X device x; i TDThe total number of time periods participating in the running analysis in a day is represented by (generally, 24 hours);
Figure BDA0002919986950000083
showing the energy conversion efficiency of the P2X plant X for making X,
Figure BDA0002919986950000084
the power consumption of the P2X device X for obtaining X at d days t of m months is shown,
Figure BDA0002919986950000085
indicating the utilization of the P2X device on d days of m monthsxAnd (5) obtaining X and storing the X.
Wherein the content of the first and second substances,
Figure BDA0002919986950000086
equation (33) represents the power consumption constraint of the P2X device, where
Figure BDA0002919986950000087
Representing the power investment capacity of P2X device x.
1-2) seasonal X energy storage annual time sequence coupling operation constraint;
based on the step 1-1), establishing a time sequence coupling operation characteristic equation of seasonal X energy storage in the time scale of the whole year as shown in formulas (3) to (4):
Figure BDA0002919986950000088
Figure BDA0002919986950000089
equation (34) represents the energy balance constraint between adjacent days during the seasonal stored energy month. Wherein Cha/Dis respectively represents the charging/discharging state of X energy storage, and p represents the transportation path of X; collection
Figure BDA0002919986950000091
Respectively representing the collection of transportation paths carried out and carried in by a P2X device X for making X;
Figure BDA0002919986950000092
representing the energy storage wear rate of P2X device X storing X,
Figure BDA0002919986950000093
indicating that P2X device X stores X reserves on d days of m months,
Figure BDA0002919986950000094
respectively expressed by the preparation of P2X equipment x on d days of m monthsX and the amount of storage and release performed,
Figure BDA0002919986950000095
represents the X traffic through the transport path p at d days m months.
The formula (35) represents the energy balance constraint between adjacent months of the P2X equipment, wherein delta represents the transportation time consumption of X between the areas, | M | represents the upper limit of the month number, the value is 12, | D |mI represents the upper limit of the day number value of the mth month; since equation (35) considers the operating constraint between m and m-1, m starts from m ═ 2. Through the monthly and daily traversal, the annual time sequence coupling constraint of the operation of the P2X equipment is established.
Setting the balance constraints of the starting reserves and the ending reserves of the P2X plant at the time scale of the whole year based on the operation constraints of the P2X plant as shown in equation (5):
Figure BDA0002919986950000096
1-3) inter-regional transport constraints for X;
1-2), adding an X transport constraint among areas as shown in a formula (6):
Figure BDA0002919986950000097
this constraint represents the amount of traffic from P2X plant x through all paths
Figure BDA0002919986950000098
The total amount stored by the current P2X device, i.e. the daily reserve, cannot be exceeded
Figure BDA0002919986950000099
1-4) for each X, the conjunctions (32) - (37) form a unified model for different types of P2X.
2) Establishing a power system planning optimization model considering the operation of P2X, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
2-1) determining an objective function of the optimization model:
min(CInv+COpe+CCur) (38)
the objective function represents a total cost minimization, where CInvRepresents annual investment cost of the power system, COpeRepresents the annual operating cost of the power system, CCurRepresenting the load shedding penalty cost. The specific expressions of the costs are as follows:
A. annual investment cost CInv
CInv＝CInv,G+CInv,W+CInv,PV+CInv,L+CInv,B+CInv,X (39)
The annual investment cost comprises annual investment C of the conventional thermal power generating unitInv,GAnnual investment of wind turbineInv,WAnnual investment of photovoltaic units CInv,PVAnnual investment of transmission line CInv,LAnnual electrochemical energy storage investment CInv,BP2X and annual investment C of seasonal energy storage equipmentInv,XWherein:
Figure BDA0002919986950000101
Figure BDA0002919986950000102
Figure BDA0002919986950000103
Figure BDA0002919986950000104
Figure BDA0002919986950000105
Figure BDA0002919986950000106
wherein G, W, PV, L, B, X respectively represent the numbers of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic power generating unit, a power transmission line, an electrochemical energy storage device and a P2X device, | G |, | W |, | PV |, | L |, | B |, | X | respectively represent the numbers of the conventional thermal power generating unit, the wind power generating unit, the photovoltaic power generating unit, the power transmission line, the electrochemical energy storage device and the P2X device, and the upper labels G, W, PV, L, B, X respectively represent the electric power device categories of the conventional thermal power generating unit, the wind power generating unit, the photovoltaic power generating unit, the power transmission line, the electrochemical energy storage device and the P2X device;
Figure BDA0002919986950000107
represents the annual unit investment cost of the g installed capacity of the conventional thermal power generating unit,
Figure BDA0002919986950000108
representing the annual unit investment cost of the installed capacity of the wind turbine,
Figure BDA0002919986950000109
represents the annual unit investment cost of the installed capacity of the PV unit,
Figure BDA00029199869500001010
represents the annual unit investment cost of the l capacity of the transmission line,
Figure BDA00029199869500001011
respectively represents the annual unit investment cost of the power capacity/energy capacity of the electrochemical energy storage device b,
Figure BDA00029199869500001012
annual unit investment costs representing power capacity/energy capacity of P2X plant x, respectively;
Figure BDA00029199869500001013
represents the investment capacity of the conventional thermal power generating unit g,
Figure BDA00029199869500001014
representing the investment capacity of the wind turbine w,
Figure BDA00029199869500001015
represents the investment capacity of the photovoltaic unit pv,
Figure BDA00029199869500001016
the investment capacity of the transmission line/is represented,
Figure BDA00029199869500001017
Figure BDA00029199869500001018
respectively representing the power investment capacity and the energy investment capacity of the electrochemical energy storage device b,
Figure BDA00029199869500001019
representing the power investment capacity and energy investment capacity of P2X plant x, respectively.
B. Annual operating costs COpe
COpe＝COpe,E+COpe,X (46)
Annual operating costs include power system annual operating cost COpe,EAnd X supply chain annual operating costs COpe,XWherein:
Figure BDA0002919986950000111
wherein the annual operating cost of the power system COpe,EMainly considering the cost of fuel for thermal power generation,
Figure BDA0002919986950000112
represents the unit fuel cost of the electricity generation of the conventional thermal power generating unit g,
Figure BDA0002919986950000113
and the generated power of the conventional thermal power generating unit g at m months, d days and t is shown.
Figure BDA0002919986950000114
Wherein the content of the first and second substances,
Figure BDA0002919986950000115
represents the unit transportation cost of X on the transportation path p;
Figure BDA0002919986950000116
represents the unit cost of charging and discharging energy of the P2X device x in the operation process,
Figure BDA0002919986950000117
represents the unit cost of supplying X by traditional fossil energy (such as coal, petroleum and other traditional fossil energy);
Figure BDA0002919986950000118
representing the amount of X transported over path p at d days of m months,
Figure BDA0002919986950000119
representing the amount of P2X device X supplied X by traditional fossil energy sources on days d of m months. The X supply chain operating costs include: daily X transportation costs through path p
Figure BDA00029199869500001110
Seasonal X energy storage charging/discharging cost
Figure BDA00029199869500001111
And daily cost of traditional fossil energy supply X
Figure BDA00029199869500001112
C. Penalty cost of load shedding
Figure BDA00029199869500001113
Wherein N represents the grid node number and | N | representsThe total number of the grid nodes, VoLL represents the unit load shedding penalty cost,
Figure BDA00029199869500001114
representing the load shedding power of the node n at d days t of m months.
2-2) determining the constraint conditions of the optimization model, specifically as follows:
2-2-1) node power balance constraints:
Figure BDA00029199869500001115
Figure BDA00029199869500001116
equation (50) represents the node power balance constraint for the power network, where the subscript n represents the grid node number; collection of
Figure BDA00029199869500001117
Figure BDA0002919986950000121
Respectively representing the topological connection relations of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic unit, electrochemical energy storage equipment and P2X equipment and a node n;
Figure BDA0002919986950000122
respectively representing a power flow reference direction of the power transmission line l and taking the node n as a line set of an initial node and a termination node;
Figure BDA0002919986950000123
respectively represents the generating power of a conventional thermal power generating unit g, a wind power generating unit w and a photovoltaic power generating unit pv at d days t of m months,
Figure BDA0002919986950000124
respectively representing the charging power and the discharging power of the electrochemical energy storage device b at the time of m months, d days and t,
Figure BDA0002919986950000125
represents the power consumed by P2X device x during the m months d days t, Fl,m,d,tRepresenting the power flow of the transmission line l at D days t of m months, Dn,m,d,tRepresenting the load power of the node n at d days t of m months,
Figure BDA0002919986950000126
represents the load shedding power of the node n at d days t of m months. Equation (51) limits the node load shedding upper limit not to exceed the node load power.
2-2-2) power transmission network constraints:
Figure BDA0002919986950000127
Figure BDA0002919986950000128
Figure BDA0002919986950000129
equation (52) is a constraint of the DC power flow characteristic equation of the transmission line, where θn,m,d,tRepresents the power angle, x, of the node n at d days t of m monthslRepresents the reactance of line l; equation (53) represents the upper and lower limits of the power angle of the node; equation (54) represents the line power ceiling constraint, where
Figure BDA00029199869500001210
Representing the upper limit of tidal current power of the line l.
2-2-3) conventional thermal power generating unit operation constraint:
Figure BDA00029199869500001211
the formula (55) is the upper and lower limit constraints of the output of the conventional thermal power generating unit, wherein,
Figure BDA00029199869500001212
and respectively representing the upper limit and the lower limit of the output power of the conventional thermal power generating unit g.
2-2-4) renewable energy output constraint:
Figure BDA00029199869500001213
Figure BDA00029199869500001214
expressions (56) to (57) represent upper and lower output limit constraints of the wind turbine and the photovoltaic generator, respectively, wherein
Figure BDA00029199869500001215
Represents the upper limit of the predicted output of the wind turbine generator w at the time of m months, d days and t,
Figure BDA00029199869500001216
and the upper limit of the predicted output of the photovoltaic unit pv at d days t of m months is shown.
2-2-5) electrochemical energy storage operation constraint:
Figure BDA0002919986950000131
equation (58) is the energy storage energy balance equation for adjacent time periods, where
Figure BDA0002919986950000132
Representing the stored energy of the electrochemical energy storage device b at d days t of m months,
Figure BDA0002919986950000133
represents the charge-discharge efficiency of the electrochemical storage energy b.
Figure BDA0002919986950000134
Figure BDA0002919986950000135
The formula (59) is the restriction of the upper and lower limits of the electrochemical energy storage charge and discharge power, and the formula (60) is the restriction of the upper and lower limits of the energy storage capacity.
Figure BDA0002919986950000136
Equation (61) is the coulomb balance constraint of the electrochemical stored energy over the cycle period.
2-2-6) P2X model and operational constraints;
taking the P2X model formulas (32) - (37) corresponding to each X formed in the step 1) as P2X models and operation constraints
2-2-7) supply chain system balance equation constraints for each X:
Figure BDA0002919986950000137
equation (62) is a separately established supply chain equilibrium equation for each X, where
Figure BDA0002919986950000138
Representing the X load demand of P2X device X corresponding to d days m months.
3) Solving the model established in the step 2);
solving the optimization model established in the soft step 2) by using Cplex, and outputting a planning configuration result, wherein the method comprises the following steps:
Figure BDA0002919986950000139
Figure BDA00029199869500001310
the optimal solution of (2) is used as the optimal value of the investment capacity of each device, and the scheduling operation optimization result comprises the following steps:
Figure BDA00029199869500001311
each year of optimized operationAnd the optimal solution of the time period is used as the optimal value of the power of each device, and the optimal planning scheme is finally obtained, so that reference is provided for the establishment of the optimal planning scheme and the scheduling operation strategy of the power system.
The P2X modeling and optimizing method for the high-proportion renewable energy power system provides technical reference for future power system optimization planning and operation simulation. The core of the method is that a unified model facing different P2X technology types is established, annual time sequence coupling operation of seasonal X storage is further considered from the time perspective, and the characteristic that X can be transported across a space range is considered from the space perspective; analyzing and depicting the operating characteristics of the power system based on the P2X technology, and embedding a power system optimization planning model to analyze the optimal configuration and the operating characteristics of the power system. Compared with the existing power system optimization planning models, the method analyzes the power system time sequence coupling operation characteristics based on seasonal X energy storage through the analytic modeling P2X electric energy preparation process, and researches the power system, an X supply chain system and a traffic network collaborative optimization planning and operation. Through the solution of the optimization model, the power designer can perform equipment optimization configuration of the power system and even the energy system according to the calculation result, analyze the annual time sequence coupling operation condition of the power system containing P2X, and provide a reference basis for investment decision. Therefore, the renewable energy of the power system is effectively consumed, and the economical efficiency and the environmental protection performance of the system operation are improved.

Claims (1)

1. A P2X modeling and optimizing method for a high-proportion renewable energy power system is characterized in that firstly, aiming at each X prepared by electric energy, P2X electric energy preparation constraint, seasonal X energy storage annual time sequence coupling operation constraint and X inter-area transfer constraint which correspond to the X are respectively constructed to form a P2X model which corresponds to each X; then establishing an electric power system planning optimization model considering P2X operation, wherein the objective function of the model is the minimization of the total cost, and the constraint conditions comprise node power balance constraint, power transmission network constraint, conventional thermal power unit operation constraint, renewable energy output constraint, electrochemical energy storage operation constraint and supply chain system balance equation constraint of each X; embedding the P2X model corresponding to each X into the model as a P2X model and operation constraints; solving the optimization model to obtain the optimal planning scheme of the power system,
wherein the method comprises the steps of:
1) respectively establishing a P2X model corresponding to each X prepared by electric energy; the method comprises the following specific steps:
1-1) constraint of P2X electric energy:
Figure FDA0003630738740000011
wherein, the superscript X represents different types of energy and substances obtained by energy conversion by utilizing the P2X technology, and Cha represents the charging state of X stored energy; subscript x represents P2X equipment number, m represents month number, d represents day number, t represents time number, and N represents grid node type; collection
Figure FDA0003630738740000012
Represents the set of grid nodes connected to P2X device x;
Figure FDA0003630738740000013
representing the total number of time periods participating in the running analysis within a day;
Figure FDA0003630738740000014
showing the energy conversion efficiency of the P2X plant X for making X,
Figure FDA0003630738740000015
the power consumption of P2X device X for making X is shown in m months, d days and t,
Figure FDA0003630738740000016
representing the quantity of X obtained and stored by using P2X equipment X on d days of m months;
wherein the content of the first and second substances,
Figure FDA0003630738740000017
wherein the content of the first and second substances,
Figure FDA0003630738740000018
represents the upper power capacity limit of the P2X plant X for the production of X;
1-2) seasonal X energy storage annual time sequence coupling operation constraint; the method specifically comprises the following steps:
energy balance constraint between adjacent days in seasonal energy storage month:
Figure FDA0003630738740000019
wherein Dis represents the energy release state of X energy storage, and p represents the transportation path of X; collection of
Figure FDA0003630738740000021
Representing the collection of transport paths carried out by P2X plant X making X,
Figure FDA0003630738740000022
representing a set of transport paths taken by a P2X plant X making X;
Figure FDA0003630738740000023
representing the energy storage loss rate of P2X device X storing X,
Figure FDA0003630738740000024
indicating that P2X device X stores X reserves on d days of m months,
Figure FDA0003630738740000025
respectively representing the amount of X obtained and stored and released by using a P2X device X on d days m months,
Figure FDA0003630738740000026
indicates passage of d days in m monthsX traffic of the transport path p;
P2X device adjacent monthly energy balance constraints:
Figure FDA0003630738740000027
wherein, delta represents the time consumed for transporting X between areas,
Figure FDA0003630738740000028
the upper limit of the month number is shown, the value is 12,
Figure FDA0003630738740000029
representing the upper limit of the value of the day number of the mth month;
the starting and ending reserves balance constraint expressions for the P2X device on the annual time scale are as follows:
Figure FDA00036307387400000210
1-3) inter-regional transport constraints of X:
Figure FDA00036307387400000211
1-4) for each X, the joint type (63) - (68) forms the P2X model corresponding to the X;
2) establishing a power system planning optimization model considering the operation of P2X, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
2-1) determining an objective function of the optimization model:
min(CInv+COpe+CCur) (69)
wherein, CInvRepresents annual investment cost of the power system, COpeRepresents the annual operating cost of the power system, CCurRepresenting a load shedding penalty cost; wherein the content of the first and second substances,
CInv＝CInv,G+CInv,W+CInv,PV+CInv,L+CInv,B+CInv,X (70)
wherein, CInv,GAnnual investment for conventional thermal power generating units, CInv,WAnnual investment for wind turbines, CInv,PVAnnual investment of photovoltaic units, CInv,LFor annual investment in transmission lines, CInv,BAnnual investment for electrochemical energy storage, CInv,XAnnual investment for P2X and seasonal energy storage equipment; the calculation expressions are respectively as follows:
Figure FDA0003630738740000031
Figure FDA0003630738740000032
Figure FDA0003630738740000033
Figure FDA0003630738740000034
Figure FDA0003630738740000035
Figure FDA0003630738740000036
wherein g, w, pv, l, b and x respectively represent the numbers of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic power generating unit, a power transmission line, electrochemical energy storage equipment and P2X equipment,
Figure FDA0003630738740000037
the number of the conventional thermal power generating units, the number of the wind power generating units, the number of the photovoltaic units, the number of the power transmission lines, the number of the electrochemical energy storage devices and the number of the P2X devices are respectively represented, and the superscripts G, W, PV, L, B and X respectively represent the types of the power devices of the conventional thermal power generating units, the conventional wind power generating units, the conventional photovoltaic units, the power transmission lines, the conventional electrochemical energy storage devices and the conventional P2X devices;
Figure FDA0003630738740000038
represents the annual unit investment cost of the g installed capacity of the conventional thermal power generating unit,
Figure FDA0003630738740000039
representing the annual unit investment cost of the installed capacity of the wind turbine,
Figure FDA00036307387400000310
represents the annual unit investment cost of the installed capacity of the PV unit,
Figure FDA00036307387400000311
represents the annual unit investment cost of the l capacity of the transmission line,
Figure FDA00036307387400000312
represents the annual unit investment cost of the power capacity of the electrochemical energy storage device b,
Figure FDA00036307387400000313
represents the annual unit investment cost of the energy capacity of the electrochemical energy storage device b,
Figure FDA00036307387400000314
representing the annual unit investment cost of the power capacity of P2X plant x,
Figure FDA00036307387400000315
annual unit investment cost representing the energy capacity of P2X plant x;
Figure FDA00036307387400000316
represents the investment capacity of the conventional thermal power generating unit g,
Figure FDA00036307387400000317
representing the investment capacity of the wind turbine w,
Figure FDA00036307387400000318
represents the investment capacity of the photovoltaic unit pv,
Figure FDA00036307387400000319
the investment capacity of the transmission line/is represented,
Figure FDA00036307387400000320
representing the power investment capacity of the electrochemical energy storage device b,
Figure FDA00036307387400000321
representing the energy investment capacity of the electrochemical energy storage device b,
Figure FDA00036307387400000322
representing the power investment capacity of P2X plant x,
Figure FDA00036307387400000323
represents the energy investment capacity of P2X plant x;
COpe＝COpe,E+COpe,X (77)
wherein, COpe,ERepresents the annual operating cost of the power system, COpe,XRepresents the annual operating cost of the X supply chain; the calculation expressions are respectively as follows:
Figure FDA0003630738740000041
wherein the content of the first and second substances,
Figure FDA0003630738740000042
represents the unit fuel cost of the electricity generation of the conventional thermal power generating unit g,
Figure FDA0003630738740000043
representing the power generation power of the conventional thermal power generating unit g at m months, d days and t;
Figure FDA0003630738740000044
wherein the content of the first and second substances,
Figure FDA0003630738740000045
represents the unit transportation cost of X on the transportation path p;
Figure FDA0003630738740000046
represents the unit cost of charging and discharging energy of the P2X device x in the operation process,
Figure FDA0003630738740000047
represents the unit cost of the traditional fossil energy supply X;
Figure FDA0003630738740000048
representing the amount of X transported over path p at d days of m months,
Figure FDA0003630738740000049
represents the amount of P2X device X supplied X by conventional fossil energy on days of m months d;
Figure FDA00036307387400000410
wherein n represents the grid node number,
Figure FDA00036307387400000411
represents the total number of the grid nodes, VoLL represents the unitThe penalty cost of the load-shedding is obtained,
Figure FDA00036307387400000412
representing the load shedding power of the node n at d days t of m months;
2-2) determining the constraint conditions of the optimization model, specifically as follows:
2-2-1) node power balance constraints:
Figure FDA00036307387400000413
Figure FDA00036307387400000414
wherein, aggregate
Figure FDA00036307387400000415
Respectively representing the topological connection relations of a conventional thermal power generating unit, a wind power generating unit, a photovoltaic unit, electrochemical energy storage equipment and P2X equipment and a node n;
Figure FDA00036307387400000416
a line set which represents the power flow reference direction of the transmission line l and takes the node n as a starting node,
Figure FDA00036307387400000417
representing a line set of a power flow reference direction of the power transmission line l by taking the node n as a termination node;
Figure FDA00036307387400000418
respectively representing the generating power of a conventional thermal power generating unit g, a wind power generating unit w and a photovoltaic power generating unit pv at d days t of m months,
Figure FDA0003630738740000051
respectively representing the charging power and the discharging power of the electrochemical energy storage device b at the time of m months, d days and t,
Figure FDA0003630738740000052
represents the power consumed by P2X device x during the m months d days t, Fl,m,d,tRepresenting the power flow of the transmission line l at D days t of m months, Dn,m,d,tRepresenting the load power of the node n at d days t of m months,
Figure FDA0003630738740000053
representing load shedding power of the node n at d days t of m months;
2-2-2) power transmission network constraints:
Figure FDA0003630738740000054
Figure FDA0003630738740000055
Figure FDA0003630738740000056
wherein, thetan,m,d,tRepresents the power angle, x, of the node n at d days t of m monthslRepresents the reactance of line l; fl L,MaxRepresenting the upper limit of the tidal current power of the line l;
2-2-3) conventional thermal power generating unit operation constraint:
Figure FDA0003630738740000057
wherein the content of the first and second substances,
Figure FDA0003630738740000058
respectively representing the upper limit and the lower limit of the output power of the conventional thermal power generating unit g;
2-2-4) renewable energy output constraint:
Figure FDA0003630738740000059
Figure FDA00036307387400000510
wherein
Figure FDA00036307387400000511
Represents the upper limit of the predicted output of the wind turbine generator w at the time of m months, d days and t,
Figure FDA00036307387400000512
representing the upper limit of the predicted output of the photovoltaic unit pv at the time of m months, d days and t;
2-2-5) electrochemical energy storage operation constraint:
Figure FDA00036307387400000513
wherein
Figure FDA00036307387400000514
Representing the electricity storage capacity of the electrochemical energy storage device b at d days t of m months,
Figure FDA00036307387400000515
represents the charge-discharge efficiency of the electrochemical stored energy b;
Figure FDA00036307387400000516
Figure FDA00036307387400000517
Figure FDA00036307387400000518
2-2-6) P2X model and operational constraints;
taking the P2X corresponding to each X obtained in the step 1) as a P2X model and operation constraint;
2-2-7) supply chain system balance equation constraints for each X:
Figure FDA0003630738740000061
wherein
Figure FDA0003630738740000062
Representing the X load demand of P2X device X corresponding to d days m months;
3) solving the model established in the step 2) to obtain
Figure FDA0003630738740000063
As an optimum value of the investment capacity of each equipment, and
Figure FDA0003630738740000064
the optimal solution of the method is used as the optimal value of the power of each device, and finally the optimal planning scheme is obtained.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1656661A (en) * 2002-03-28 2005-08-17 罗伯绍控制器公司 Energy management system and method
CN105528466A (en) * 2014-09-28 2016-04-27 国家电网公司 Wind power optimal planning modeling method considering adaptability and economy of power system
WO2018059096A1 (en) * 2016-09-30 2018-04-05 国电南瑞科技股份有限公司 Combined decision method for power generation plans of multiple power sources, and storage medium
CN110071505A (en) * 2019-06-04 2019-07-30 清华大学 The power transmission network enlarging of the access containing large-scale wind power configures joint planing method with energy storage
CN110460109A (en) * 2019-08-21 2019-11-15 清华大学 Passway for transmitting electricity increases the analysis method and device of capacity newly between regional power grid

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1656661A (en) * 2002-03-28 2005-08-17 罗伯绍控制器公司 Energy management system and method
CN105528466A (en) * 2014-09-28 2016-04-27 国家电网公司 Wind power optimal planning modeling method considering adaptability and economy of power system
WO2018059096A1 (en) * 2016-09-30 2018-04-05 国电南瑞科技股份有限公司 Combined decision method for power generation plans of multiple power sources, and storage medium
CN110071505A (en) * 2019-06-04 2019-07-30 清华大学 The power transmission network enlarging of the access containing large-scale wind power configures joint planing method with energy storage
CN110460109A (en) * 2019-08-21 2019-11-15 清华大学 Passway for transmitting electricity increases the analysis method and device of capacity newly between regional power grid

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
面向可再生能源消纳的电化工（P2X）技术分析及其能耗水平对比;李佳蓉等;《全球能源互联网》;20200125;第3卷(第01期);全文 *
面向可再生能源高比例消纳的综合能源系统优化规划模型研究;张子阳等;《可再生能源》;20200818;第38卷(第08期);全文 *

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